M
Mehrdad Tahmasebi
Researcher at Islamic Azad University
Publications - 15
Citations - 99
Mehrdad Tahmasebi is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Load profile & Demand response. The author has an hindex of 4, co-authored 13 publications receiving 60 citations. Previous affiliations of Mehrdad Tahmasebi include Universiti Tenaga Nasional.
Papers
More filters
Journal ArticleDOI
Optimal Grid-Connected PV System for a Campus Microgrid
TL;DR: The results demonstrate optimal HRES combinations for the campus microgrid comprises of 50 kWp of PV generations with 50 kW inverter, however, inclusion of 576 kWh battery storage system will increase the NPC but has higher RE penetration.
Journal ArticleDOI
Self-Scheduling of Wind Power Generation with Direct Load Control Demand Response as a Virtual Power Plant
TL;DR: This work focused on the economic operation of CVPP consisting of WPP and DLC in a competitive electricity market and the WPP intermittent compensation and used self-scheduling, SS, method to derive maximum expected profit from the Energy Markets.
Journal ArticleDOI
Optimal Operation of Stand-Alone Microgrid Considering Emission Issues and Demand Response Program Using Whale Optimization Algorithm
Mehrdad Tahmasebi,Jagadeesh Pasupuleti,Fatemeh Mohamadian,Mohammad Shakeri,Josep M. Guerrero,M. Reyasudin Basir Khan,Muhammad Shahzad Nazir,Amir Safari,Najmeh Bazmohammadi +8 more
TL;DR: The findings indicate that the whale optimization algorithm outperforms the other known algorithms such as imperialist competitive and genetic algorithms, as well as particle swarm optimization, and shows that the use of DRPS has a significant impact on the costs of operation and emissions.
Proceedings ArticleDOI
Smart Buildings Aggregator Bidding Strategy as a Negawatt Demand Response Resources in the Spinning Reserve Electricity Market
TL;DR: This paper has proposed a new bidding strategy for the smart buildings aggregator as a “Negawatt Demand Response Resources” in the electricity market based on self-scheduling method which is formulated as a linear model.
Journal ArticleDOI
Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market
Mohammad Tolou Askari,Mohd Zainal Abdin Ab Kadir,Mohd Zainal Abdin Ab Kadir,Mehrdad Tahmasebi,Ehsan Bolandifar +4 more
TL;DR: A novel framework for the estimation of optimal investment strategies for combined wind-thermal companies is proposed and is implemented in the hypothetical restructured power market using the IEEE reliability test system (RTS).